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Dijkstra's algorithm to find the nearest vaccine location.

Jason1, Melvin Siever1, Alvin Valentino1

  • 1Computer Science Department, School of Computer Science Bina Nusantara University Jakarta, 11480, Indonesia.

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Summary
This summary is machine-generated.

This study implements Dijkstra's algorithm to find the nearest COVID-19 vaccine locations, visualizing the shortest path using Google Maps API. The research highlights the algorithm's efficiency in determining optimal routes for public health accessibility.

Keywords:
COVID-19Dijkstra AlgorithmLocationShortest pathVaccination

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Area of Science:

  • Computer Science
  • Public Health
  • Geographic Information Systems

Background:

  • The COVID-19 pandemic increased demand for accessible vaccine locations.
  • Dijkstra's algorithm is a standard method for solving the shortest path problem.
  • Efficient route calculation is crucial for public health logistics.

Purpose of the Study:

  • To calculate and implement Dijkstra's algorithm for finding the nearest vaccine locations.
  • To visualize the shortest path to vaccine sites using Google Maps API.
  • To assess the practical application of Dijkstra's algorithm in a real-world public health scenario.

Main Methods:

  • Graph theory principles were applied to represent routes.
  • Route data was acquired using Google Maps.
  • Dijkstra's algorithm was implemented using HTML, JavaScript, and the Google Maps API.
  • Manual calculations and graph explanations were used for initial testing.

Main Results:

  • The study successfully calculated and visualized the shortest paths to vaccine locations.
  • Implementation demonstrated the Dijkstra algorithm's effectiveness in identifying optimal routes.
  • A limitation was identified regarding the detailed representation of road turns as vertices and edges.

Conclusions:

  • Dijkstra's algorithm provides an efficient method for finding nearest vaccine locations.
  • Visualizing routes with Google Maps API enhances accessibility and user understanding.
  • Further refinement is needed to accurately model complex road networks for optimal pathfinding.